The invention relates to enterprise computing environments, and more particularly, to computing environments for enterprise business planning.
More than ever before, enterprises are charged with establishing accurate forecasts for enterprise operations. Failing to meet established expectations can have significant negative impact on the enterprise in the areas of cash flow, stock price, liquidity, and investor faith, among other areas. Examples of enterprise planning activities for which accuracy is critical include revenue forecasting, inventory management, resource planning, and the like. Enterprise business planning, however, is a difficult and expensive task that often produces inaccurate results.
Conventionally, businesses have taken either a xe2x80x9ctop-downxe2x80x9d or a xe2x80x9cbottom-upxe2x80x9d approach to enterprise planning. In xe2x80x9ctop-downxe2x80x9d planning, businesses identify fundamental business targets, such as average product price, cost per employee, and the like, and push the targets down through the hierarchical structure of the corporation. In contrast, xe2x80x9cbottom-upxe2x80x9d planning involves the aggregation of low-level forecasts from the lowest cost centers of an organization. For budget planning, for example, management personnel may be required to periodically forecast expenses, and allocate the expenses to a number of categories, such as advertisement, travel, and salaries. However, the bottom-up forecasts rarely, if ever, reconcile with top-down business targets.
This information has typically been collected using paper or, more recently, electronic forms, such as an electronic template created with a spreadsheet software program. This often leaves the financial department of the enterprise with the difficult task of consolidating uncoordinated plans that have been compiled using inconsistent assumptions and varying business logic.
More recently, large computer systems have been used to collect the data via an enterprise network. The computer systems typically consolidate data collected from the various enterprise users using time-consuming, offline batch processing during xe2x80x9coffxe2x80x9d hours. This offline consolidation can lead to significant time delays between the collection of the data from a user, and the consolidation of the collected data with other data collected from the enterprise. As a result, such systems often present users an inaccurate view of the actual, aggregated data for the enterprise activity being forecasted. This may lead the users to provide incorrect data, or erroneously modify their input. Furthermore, the users may be unsure as to which numbers are the xe2x80x9crightxe2x80x9d numbers for the enterprise, and may generally doubt the integrity of the results. This slow process of data collection and offline consolidation can be particularly problematic for a heavily deadline-oriented activity like enterprise planning.
The invention is directed to enterprise planning techniques that improve the accuracy and predictability of budget planning within large organizations by enabling organizations to reconcile corporate financial models and organizational targets with detailed forecasts in real-time. In particular, the techniques make use of an enterprise planning database system having a transactional data area for real-time interaction with enterprise users, and a relational data area for detailed statistical analysis and report generation.
According to the techniques, an enterprise planning system enables and automates the reconciliation of top-down targets with detailed bottom-up forecasts for an enterprise. Generally, the enterprise planning system provides three stages of enterprise planning: (1) a modeling stage, (2) a contribution stage, and (3) a reconciliation stage. During the modeling stage, high-level enterprise managers or executives, referred to as analysts, define organizational targets, and build planning models for the enterprise. Next, during the contribution phase, a set of defined contributors interacts with the enterprise planning system and provides detailed forecasts in the form of contribution data. During the reconciliation phase, the enterprise planning system automates the reconciliation of the forecast data with the organizational targets.
During this process, the enterprise planning system operates in accordance with the defined model to provide a hierarchical planning process having multiple reconciliation levels. At each level, the enterprise planning system presents the contribution data to enterprise reviewers, as defined by the hierarchical model, and requires that the reviewer reconcile the target data with the forecast data. Each reviewer may, for example, reject or accept the contribution data in view of corporate targets provided by the analysts.
As the contributors provide the contribution data, the enterprise planning system automatically aggregates the contribution data across the enterprise in real-time, and presents the aggregated data to reviewers for acceptance or rejection. This process continues until the contribution data is ultimately approved by the reviewers associated with the highest level of the organizational hierarchy, thereby ensuring that the contribution data from the contributors reconciles with corporate targets.
In one embodiment, a system comprises a database having a relational data area and a transactional data area, and a server to store within the transactional data area contribution data received from a set of enterprise contributors, and to publish the contribution data from the transactional data area to the relational data area. The transactional data area may include a set of contribution slots and aggregations slots hierarchically related in accordance with an enterprise model. The relational area may comprise a set of related tables defined in accordance with the model.
In another embodiment, a method comprises receiving contribution data from a contributor of an enterprise in accordance with a multi-level enterprise model, and storing the contribution data for the contributor within a transactional area of a database. The method further comprises publishing the contribution data from the transactional area to a relational area of the database, and generating a report from the contribution data of the relational area of the database.
The invention may offer one or more advantages. For example, the techniques described herein may improve the accuracy and predictability of enterprise planning by enabling organizations to reconcile corporate models and organizational targets with detailed forecasts in real-time. The techniques may provide a platform that delivers collaborative, real-time planning capabilities, without requiring offline consolidation and aggregation of forecasts. Because the enterprise planning system can aggregate contribution data in real-time, all users can be presented with an accurate, up-to-date view of the numbers. The system provides rapid response regardless of the number of enterprise users involved in the planning, thus providing precise planning information.
Further, the architecture described herein can readily scale to thousands of users, and may be designed around best planning practices. In this manner, the system may used to centrally manage all planning information across operating units and systems within the enterprise, thus creating a xe2x80x9cplanning hub.xe2x80x9d Consequently, users can work from a single pool of planning data, and can be assured of the integrity of the data.
In addition, the techniques promote high user-participation across the enterprise, allowing planning cycles to be reduced, e.g., from months to weeks, and best practices, like rolling forecasting, to be quickly enabled.
The details of one or more embodiments of the invention are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the invention will be apparent from the description and drawings, and from the claims.